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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: beit-base-patch16-224-pt22k-ft22k-rim_one-new |
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results: |
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- task: |
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type: image-classification |
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name: Image Classification |
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dataset: |
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type: rimonedl |
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name: RIM ONE DL |
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split: test |
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metrics: |
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- type: f1 |
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value: 0.9197860962566845 |
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name: F1 |
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- task: |
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type: image-classification |
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name: Image Classification |
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dataset: |
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type: rim one |
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name: RIMONEDL |
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split: test |
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metrics: |
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- type: precision |
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value: 0.9247311827956989 |
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name: precision |
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- type: recall |
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value: 0.9148936170212766 |
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name: Recall |
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- type: accuracy |
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value: 0.8972602739726028 |
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name: Accuracy |
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- type: roc_auc |
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value: 0.8901391162029461 |
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name: AUC |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# beit-base-patch16-224-pt22k-ft22k-rim_one-new |
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4550 |
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- Accuracy: 0.8767 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 0.73 | 2 | 0.2411 | 0.9178 | |
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| No log | 1.73 | 4 | 0.2182 | 0.8973 | |
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| No log | 2.73 | 6 | 0.3085 | 0.8973 | |
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| No log | 3.73 | 8 | 0.2794 | 0.8973 | |
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| 0.1392 | 4.73 | 10 | 0.2398 | 0.9110 | |
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| 0.1392 | 5.73 | 12 | 0.2925 | 0.8973 | |
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| 0.1392 | 6.73 | 14 | 0.2798 | 0.9110 | |
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| 0.1392 | 7.73 | 16 | 0.2184 | 0.9178 | |
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| 0.1392 | 8.73 | 18 | 0.3007 | 0.9110 | |
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| 0.0416 | 9.73 | 20 | 0.3344 | 0.9041 | |
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| 0.0416 | 10.73 | 22 | 0.3626 | 0.9110 | |
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| 0.0416 | 11.73 | 24 | 0.4842 | 0.8904 | |
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| 0.0416 | 12.73 | 26 | 0.3664 | 0.8973 | |
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| 0.0416 | 13.73 | 28 | 0.3458 | 0.9110 | |
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| 0.0263 | 14.73 | 30 | 0.2810 | 0.9110 | |
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| 0.0263 | 15.73 | 32 | 0.4695 | 0.8699 | |
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| 0.0263 | 16.73 | 34 | 0.3723 | 0.9041 | |
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| 0.0263 | 17.73 | 36 | 0.3447 | 0.9041 | |
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| 0.0263 | 18.73 | 38 | 0.3708 | 0.8904 | |
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| 0.0264 | 19.73 | 40 | 0.4052 | 0.9110 | |
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| 0.0264 | 20.73 | 42 | 0.4492 | 0.9041 | |
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| 0.0264 | 21.73 | 44 | 0.4649 | 0.8904 | |
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| 0.0264 | 22.73 | 46 | 0.4061 | 0.9178 | |
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| 0.0264 | 23.73 | 48 | 0.4136 | 0.9110 | |
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| 0.0139 | 24.73 | 50 | 0.4183 | 0.8973 | |
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| 0.0139 | 25.73 | 52 | 0.4504 | 0.8904 | |
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| 0.0139 | 26.73 | 54 | 0.4368 | 0.8973 | |
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| 0.0139 | 27.73 | 56 | 0.4711 | 0.9110 | |
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| 0.0139 | 28.73 | 58 | 0.3928 | 0.9110 | |
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| 0.005 | 29.73 | 60 | 0.4550 | 0.8767 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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